Sequential Tasks Shifting for Participation in Demand Response Programs

Mahsa Khorram, Pedro Faria, Zita Vale and Carlos Ramos
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Mahsa Khorram: GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal
Pedro Faria: GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal
Zita Vale: IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal
Carlos Ramos: GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, IPP—Polytechnic Institute of Porto, Rua DR. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal

Energies, 2020, vol. 13, issue 18, 1-16

Abstract: In this paper, the proposed methodology minimizes the electricity cost of a laundry room by means of load shifting. The laundry room is equipped with washing machines, dryers, and irons. Additionally, the optimization model handles demand response signals, respecting user preferences while providing the required demand reduction. The sequence of devices operation is also modeled, ensuring correct operation cycles of different types of devices which are not allowed to overlap or have sequence rules. The implemented demand response program specifies a power consumption limit in each period and offers discounts for energy prices as incentives. In addition, users can define the required number of operations for each device in specific periods, and the preferences regarding the operation of consecutive days. In the case study, results have been obtained regarding six scenarios that have been defined to survey about effects of different energy tariffs, power limitations, and incentives, in a laundry room equipped with three washing machines, two dryers, and one iron. A sensitivity analysis of the power consumption limit is presented. The results show that the proposed methodology is able to accommodate the implemented scenario, respecting user preferences and demand response program, minimizing energy costs. The final electricity price has been calculated for all scenarios to discuss the more effective schedule in each scenario.

Keywords: demand response; electricity tariffs; load shifting; load scheduling; time of use (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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